## Direct versus Interpolated Fitting

Local regression to obtain a predicted value at a given point in the
predictor space is done by doing a least squares fit using all data
points in a local neighborhood of the given point. This method is
computationally expensive because a local neighborhood must be
determined and a least squares problem solved for each point at which a
fitted value is required. A faster method is to obtain such fits
at a representative sample of points in the predictor space and
to obtain fitted values at all other points by interpolation.
PROC LOESS can fit models using either of these two paradigms.
By default, PROC LOESS uses fitting at a sample of points and
interpolation. The method fitting a local model at every data point
is selected by specifying the DIRECT option in the MODEL statement.

Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.